def get_primitives(cls, **primitive_kwargs) -> [CNNPrimitive]:
act = dict(act_fun='relu', order='act_w_bn')
df = dict(act_inplace=False, bn_affine=True, use_bn=True)
return [
CNNPrimitive(cls=SepConvLayer,
kwargs=dict(k_size=3, dilation=1, **act, **df),
stacked=2),
CNNPrimitive(cls=SepConvLayer,
kwargs=dict(k_size=5, dilation=1, **act, **df),
stacked=2),
CNNPrimitive(cls=SepConvLayer,
kwargs=dict(k_size=3, dilation=2, **act, **df)),
CNNPrimitive(cls=SepConvLayer,
kwargs=dict(k_size=5, dilation=2, **act, **df)),
CNNPrimitive(PoolingLayer,
kwargs=dict(k_size=3,
pool_type='max',
act_fun=None,
order='w_bn',
**df)),
CNNPrimitive(PoolingLayer,
kwargs=dict(k_size=3,
pool_type='avg',
act_fun=None,
order='w_bn',
**df)),
StrideChoiceCNNPrimitive([
CNNPrimitive(cls=SkipLayer, kwargs=dict()),
CNNPrimitive(cls=FactorizedReductionLayer,
kwargs=dict(**act, **df))
]),
CNNPrimitive(cls=ZeroLayer, kwargs=dict()),
]
def get_primitives(cls, **primitive_kwargs) -> [CNNPrimitive]:
act = dict(act_fun='relu',
order='act_w_bn',
act_inplace=False,
bn_affine=False,
use_bn=True)
return [
CNNPrimitive(cls=ZeroLayer, kwargs=dict()),
StrideChoiceCNNPrimitive([
CNNPrimitive(cls=LinearTransformerLayer, kwargs=dict()),
CNNPrimitive(cls=FactorizedReductionLayer, kwargs=dict(**act))
]),
CNNPrimitive(cls=ConvLayer,
kwargs=dict(k_size=1, dilation=1, **act)),
CNNPrimitive(cls=ConvLayer,
kwargs=dict(k_size=3, dilation=1, **act)),
CNNPrimitive(PoolingConvLayer,
kwargs=dict(k_size=3,
pool_type='avg',
act_fun=None,
order='w',
bn_affine=False,
use_bn=False,
bias=False)),
]
def get_primitives(cls, **primitive_kwargs) -> [CNNPrimitive]:
act = dict(act_fun='relu', order='act_w_bn')
df = dict(act_inplace=False, bn_affine=True, use_bn=True)
dfnb = df.copy()
dfnb['use_bn'] = False
return [
CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=3, dilation=1, **act, **df), stacked=2),
CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=5, dilation=1, **act, **df), stacked=2),
CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=3, dilation=2, **act, **df)),
CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=5, dilation=2, **act, **df)),
DifferentConfigPrimitive(
CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='max', act_fun=None, order='w_bn', **df)),
CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='max', act_fun=None, order='w', **dfnb))),
DifferentConfigPrimitive(
CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='avg', act_fun=None, order='w_bn', **df)),
CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='avg', act_fun=None, order='w', **dfnb))),
StrideChoiceCNNPrimitive([
CNNPrimitive(cls=LinearTransformerLayer, kwargs=dict()),
CNNPrimitive(cls=FactorizedReductionLayer, kwargs=dict(**act, **df))
]),
]